报告人工智能在现实世界

1、An Economist Intelligence Unit briefing paperARTIFICIAL INTELLIGENCE IN THE REAL WORLDThe business case takes shapeSponsored byArtificial intelligence in the real world:The business case takes shapeContentsAbout the report2Executive summary3Introduction51. Testing the waters The AI businessindex Gat

2、hering momentumCase study 1: Algorithms for your evening wear78892.Hopes and expectations Theshapeofreturnstocome Artificially intelligent decisionsCase study 2: Creating a new healthcare market with AICase study 3: AI in financial markets: Risk agent orrisk minimiser?Case study 4: Ocados “flying sw

3、arms of intelligent robots”1011111214153.Industry perspectives on the AI impact174.Rising to the challengesCost and data Culture skirmishesCasestudy5:AIvisionsformanufacturing191920225.AquestionofdisruptionHappier employees?23246.Conclusion: Embracing the unknown261 The Economist Intelligence Unit L

4、imited 2016Artificial intelligence in the real world:The business case takes shapeAbout the reportRalf Herbrich, director of machine learning, Amazon(Germany)Artificial intelligence in the real world: The businesscase takes shape is a report from The Economist Intelligence Unit (EIU) sponsored by Wi

5、pro Limited. The report was written by Denis McCauley and edited by Charles Ross. It draws upon a survey conducted in the second half of 2016 of 203 executives around the globe. Respondents were evenly split among the financial services, manufacturing, retailing, as well as the health and life scien

6、ces industries. Just less than half (48%) had an annual global revenue of greater than US$1bn. C-level executives formed 50% of the sample, and those located in Asia-Pacific (35%) and North America (36%) formed the majorityof respondents.Matthew Howard, European lead, IBM Watson Health(UK)Jerry Kapl

7、an, visiting lecturer, Stanford University(USA)Frank Kirchner, head, Robotics Innovation Center, German Research Center for Artificial Intelligence(Germany)YannLeCun, director, AI research,(USA)Markus Lorenz, partner and managing director,Boston Consulting Group (Germany)To complement the survey, Th

8、e Economist Intelligence Unit conducted in-depth interviews with the following executives and AI experts from the industries underinvestigation (listed alphabetically by surname):Per Vegard Nerseth, managing director, BusinessUnit Robotics, ABB (Switzerland)Matteo Berlucchi, chief executive officer,

9、Your.MD (UK)John Straw, AI venture capitalist (UK)JaredTeo, seniorprogramofficer,HealthInnovationFund,California Health CareFoundation(USA)Paul Clarke, chieftechnology officer, Ocado(UK)Eric Colson, chiefalgorithms officer, Stitch Fix(USA)Gerrit van Wingerden, managing director,ToraTrading Services

10、(Japan)Chris Gelvin, chief operating officer, Group COOfunctions, UBS (Switzerland)The EIU bears sole responsibility for the editorialcontent of this report. The findings do not necessarily reflect the views of the sponsorBen Goertzel, chief scientist, Aidyia (Hong Kong)James Hendler, director,titut

11、e for DataNote that not all answers add up to 100%, either because of rounding or because respondents wereable to provide multiple answers to some questions.Exploration and Applications, Rensselaer Polytechnictitute (USA)All monetaryamounts arein USdollars.2 The Economist Intelligence Unit Limited 2

12、016Artificial intelligence in the real world:The business case takes shapeExecutive summaryArtificial intelligence (AI) is no longer the future. For businesses, it is the here and now, and this study conducted by The Economist Intelligence Unit makes clear that executive suites and boardrooms around

13、 the world see it as such. They might be expected to be wary, given that much is unknown, even amongst scientists, about how AI capabilities might develop in the coming years. Or that policymakers and regulators have barely begun tostudy its potential implicationsfor markets and workforces.Many busi

14、ness leaders certainly expect AI to be disruptive. More than 40% of those surveyed for the study anticipate that AI will start displacing humans from some jobs in their industry within the next five years. Slightly more think their own role will be changed by AI in the same time frame. But they see

15、this more as augmentation than marginalisation. An overwhelming majority believe AI will make their job easier and help improve their own performance. They clearly believe it will do the same for the businesses they manage.Following are other key findings from the research:The pace of adoption is qu

16、ickening. AI will be “actively implemented” in their companies within thenextthreeyears,accordingto75%ofsurveyed executives. Another 3% say this is already the case. The pace will remain the quickest in North America (active implementation in 84% of firmsthere) and, in industry terms, inretail (also

17、 84%).The purpose of this study has been to gauge corporate attitudes toward AI in different regions and different industries. Based on a global survey of 203 senior executives, it finds that, especially in North America, companies in health and life sciences, in retail, in manufacturing and in fina

18、ncial services are actively testing the waters. Amongst this group, AI technologies andapplications arein the exploratory phase at around one-third of companies, but another third have moved on to experimentation, and one- tenthhavebeguntoutiliseAIinlimitedareas.Asmallhandful (2.5%) have even deploy

19、ed it widely.North America and the health sector lead the way. Converting the survey results into an index, the AIimplementation scoreis2.40ona1-5scale, where 1=nascent, 2=exploratory, 3=experimental, 4=applied and 5=deployed. North Americancompanies in the study have advanced furthest3 The Economis

20、t Intelligence Unit Limited 2016Defining AIThe term artificial intelligence (AI) refers to a set of computer science techniques that enable systems to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision- making and language translation. Machin

21、e learning and deep learning are branches of AI which, based on algorithms and powerful data analysis, enable computers to learn and adapt independently. For ease of reference we will use “artificial intelligence”, or AI, throughout this report to refer to machine learning, deep learning and other r

22、elated techniques and technologies.Artificial intelligence in the real world:The business case takes shapewith AI (a score of 2.61) as, amongst industries,have health and life sciences (2.53) and retail firms (2.50).Efficiency and flexibility garetailers and manufacturers.beckonforRespondentsfrom th

23、ese sectors seek improvements inoperating efficiency as their chief benefit fromCompetitionor theanticipationofitisAI. Manufacturers efficiency gamay initiallyspurring companies on. The spectre of established or new technology companies using AI to enter and disrupt their markets is leading business

24、es to advance their own AI plans. Delaying these will make them vulnerable to new tech entrants, say 43% of survey respondents. Almost half (46%) are more worried about AI-based competition fromstart-ups rather than incumbents.be realised not on the production floor but in areas such as predictive m

25、aintenance and product design. Some retailers, meanwhile (including one profiled in this report), are putting ambitious plans in place to streamlinelogistics and deliverywith the help of AI technologies.Cost, data quality and cultural resistance hold companies back. Of the numerous practical challen

26、ges to AI implementation, cost figures most prominently, especially among manufacturers. Smaller companies can manage costs, however, by using third-party cloud platforms, developers can also take advantage of open-source AI platforms that are becoming available. Issues with data availability and qu

27、ality will take longer for some organisations, particularly in healthcare, to remedy. Cultural resistance to change may be the toughest nut to crack, but many companies are looking to sidestep internal silos with external help, including from partnerships and fromopen innovation.Better user experien

28、ce is the keyprize formany. AI implementation may help some firms to boost revenue, their operating efficiency or their marg . However, better user experience is the main benefit many executives especially those in the health sector look for. Healthcare companies are today using AI to deliver self-s

29、ervice diagnostic services to users. One profiled in this report uses an AI-based mobile app to diagnose, and provide advice about, users non-acute health complaints. Users benefit from faster diagnosis; GPs stand to benefit alsofrom shorter queues and thus moretime to spend with patients.Betterdeci

30、sions should also result. More accurate decision-making is another desired outcome, a benefit particularly sought by financial services providers. AI-driven algorithms are actively being put to work now, for example, in equity trading and some areas of investment management. AIs advantage, says one

31、trader interviewed for this study, is about the accuracy of investment decisions rather than about their speed. Deliberate but more accurate decisions should ultimately mean better returns and reduced risk.Building the AI business case is anything but straightforward. This is complicated, say around

32、 29% of respondents, by the fact that AItechnologies and applications are not yet mature.Much remaunknown about how they willdevelop,whichmayalsoexplainwhyanother30%say senior management lack an understanding ofAI,furtherhindering the businesscase.4 The Economist Intelligence Unit Limited 2016Artifi

33、cial intelligence in the real world:The business case takes shapeIntroductionScientists and academics sat up and took notice in 2016 when Alpha Go, Google DeepMinds AI-driven computer, won its five-match series aga t Lee Se- dol, the reigning world champion in Go, the ancient Asian board game. Busin

34、ess leaders should also have paid heed. Alpha Gos victory demonstrated in a very public way the learning capacity that AI-based technologies now possess. Humans didnt teach the computerit taught itself how to master the game byplaying it millions of times with anothercomputer (through a set of techn

35、iques called “deep learning”),and independently responded to Mr Lees moves.Technology companies are busily hiring AI expertsandome cases acquiring start-upsto perfect real-world AI-based applications. Firms in other industries are doing the same. “Were seeing a burst of energy in machine learning, d

36、eeplearningandother kinds of AI,” confirms Ben Goertzel, chief scientist at Aidyia, an AI-powered hedge fund based in Hong Kong. “Everymajor financial firm is hiring loads of AI experts now.”“AfterGoogles AIsuccess with Go, alot of businesses who werenot especially looking into deep learningarenowdo

37、ingso and will be piloting with it soon.”Machine learning, a subcategory of AI techniques which automate the learning process through algorithms and the super-powered analysis of data, has been around since the 1950s. Business applications were trialled in the financial industry asearly as the 1980s

38、 but did not go far. In recent years,Gerrit van Wingerden, managing director, Tora Trading Servicesadvancescience combined with huge increases inOpen-source platforms of the type Mr LeCunmentioned are likely to add momentum to AI(and declining prices of) computing power, swelling oceans of data and

39、increasingly sophisticated analytics have for all practical purposes made machinelearning and AI business-ready.development. Google, Amazon, Microsoftand other technology powerhouses have all made public many of their AI algorithms and invited third- party organisations and independent developers to

40、 try and improve them. (Examples are Googles TensorFlow framework and Amazons deep-learningDSSTNE platform.)It also helps that expertise in the field is now available to companies. “AI was very difficult to do for most companies until now partly because the number ofexperts in the field was extremel

41、y small,” explaYann LeCun, director of AI research at,AI is still in its early days in business, however, anda social media giant. “This shortage is easing, as even young graduates now have knowledge of AI techniques. Therearealsotools and platforms being built for people who are not yet experts to

42、get startedon developing AI applications.”much remaunknown about where it will takecompanies and their employeesan apprehensionheld by many of our survey respondents and interviewees. Its imperfections, and the related5 The Economist Intelligence Unit Limited 2016Artificial intelligence in the real

43、world:The business case takes shapedownsides, were demonstrated not long after the Alpha Go victory with Microsofts abortive launch ofits AI-powered Tay “chatbot”. Designed to conversewithusers about Microsoft services, the botwas quickly overwhelmed with abusive language and offensive comments, bac

44、kfiring badly on the company. The first highway fatality believed to result from an error in the self-driving mechanism of a car, inMay 2016,1 has added to the apprehensions.“AIsystems are already better than all but a very few people and also muchmore reliable.Theyrenotgoing togetdrunkand fail tosh

45、ow up atwork. Theyre notgoingto embezzle money. Theyre not going to quitand go work for someone else.”Ben Goertzel, chief scientist, AidyiaLonger term concerns revolve around the future successes of AI rather than its failures. Some economists, for example, fear that automation powered by data and A

46、I technologies will lead to the large-scale displacement of humans fromthe workplace.2Notwithstanding such fears, companies are actively testing the waters with AI in a number of different fields, as our research demonstrates. Pilots as well as some service introductions arenotdifficult to find ever

47、al industries. Are companies placing hard bets on AIs business potential or merely hedging them? This report explores the plans for, and hopes and fears about, AI in boardrooms and executive offices across the business world, with a focus onthe health and life sciences, retail, financial andmanufact

48、uring sectors.1 The accident,occurring in the US state of Florida, involveda TeslaMotorselectriccarbeingoperatedTech”, Scientific American, July 1, 2016.elf-drivingmode.“What the First DriverlessCar FatalityMeansfor Self-Driving2 The most prominent exposition of this argument is found in “The Future

49、 of Employment:How susceptibleare jobs to computerisation?”, an academic paper published in 2013 by Oxford UniversityprofessorsCarl Benedikt Frey and Michael Osborne.6 The Economist Intelligence Unit Limited 2016Artificial intelligence in the real world:The business case takes shape1Testing the wate

50、rsWhen new families of technology grab the headlines, business leaders often get anxious. “Is this just another round of tech hype?”, they may ask themselves, “Or isthisoneforreal?” Judgingbytheresultsofourresearch,One taking it seriously is Paul Clarke, chief technology officer at Ocado, a UK-based

51、onlinegrocer. “AI has to be the centre of everything we do now. I am sending thatmessage toall of the technologyteams in Ocado. Previously the message would have been Collect all data and make sure everything is measurable. The new message is Collect the data and make sureeverything is architected f

52、or AI from day one.”executiveseveral industries are taking AI seriously.“Were exploring AI applications in various parts of UBS. Were taking a stepwise approach, putting in the building blocksthe control frameworks, the technology, centres of expertiseand making sure we have use cases to help us fle

53、sh outour thinkingacross allour businesses.”Few companies are currently as resolute about AI as Ocado, but many are testing the waters. Most of those in the survey are at early stages of work with it. Just over one-third of respondents companies are experimenting with AI technologies in 1-2 areas of

54、 operation. About one-tenth have begun to utilise AI in a limited fashion. A small number (2.5%) even say their firms have deployed AI widely in their operations. And exploratory research is under way for anotherthird of respondents.Chris Gelvin, chief operating officer, Group COO functions, UBS7 Th

55、e Economist Intelligence Unit Limited 2016REGIONALINDUSTRYFigure 1: The US and the healthcare sector lead the way in AI applicationAI implementation score: regional vs. industry comparison(Scale: 1=nascent, 2=exploratory, 3=experimental, 4=applied, 5=deployed)OverallNorth America2.61EMEA2.03Asia-Pac

56、i c1.46Health & life sciences2.53Retail2.50Manufacturing2.38Financial services2.2001.002.003.00Artificial intelligence in the real world:The business case takes shapeThe AI business indexthis study. Both Jerry Kaplan, a visiting lecturer at Stanford University in California, and James Hendler,direct

57、or of thetitute for Data Exploration andExpressed in an index, the AI implementation score across all the firms represented in our survey is 2.40 on a 1-5 scale, where 1=nascent, 2=exploratory, 3=experimental, 4=applied and 5=deployed. This signifies a transition for many firms from exploratoryresearch to active experimentation.Applications at Rensselaer Polytechnictitutein Troy, New York, believe that in the medium termhealthcare provision holds brighter prospects for AI application than other fields.For Mr Kaplan (autho